Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “complex diseases”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources
PubMed1999

Selection of a C5a receptor antagonist from phage libraries attenuating the inflammatory response in immune complex disease and ischemia/reperfusion injury.

A C5a-receptor antagonist was selected from human C5a phage display libraries in which the C terminus of des-Arg74-hC5a was mutated. The selected molecule is a competitive C5a receptor antagonist in vitro and in vivo. Signal transduction is interrupted at the level of G-protein activation. In addition, the antagonist does not cause any C5a receptor phosphorylation. Proinflammatory properties such as chemotaxis or lysosomal enzyme release of differentiated U937 cells, as well as C5a-induced changes in intracellular Ca2+ concentration of murine peritoneal macrophages, are inhibited. The in vivo efficacy was evaluated in three different animal models of immune complex diseases in mice, i.e., the reverse passive Arthus reaction in the peritoneum, skin, and lung. The i.v. application of the C5a receptor antagonist abrogated polymorphonuclear neutrophil accumulation in peritoneum and markedly attenuated polymorphonuclear neutrophil migration into the skin and the lung. In a model of intestinal ischemia/reperfusion injury, i.v. administration of the C5a receptor antagonist decreased local and remote tissue injury: bowel wall edema and hemorrhage as well as pulmonary microvascular dysfunction. These data give evidence that C5a is an important mediator triggering the inflammatory sequelae seen in immune complex diseases and ischemia/reperfusion injury. The selected C5a receptor antagonist may prove useful to attenuate the inflammatory response in these disorders.

Amino Acid Substitution↗
PubMed1997

[Basic and clinical studies on pathogenesis of pulmonary Mycobacterium avium complex disease].

I have studied pathogenesis of pulmonary Mycobacterium avium complex disease (PMAC), using mouse and human alveolar macrophage (PAM) model of the infection as well as clinical evaluations. The mouse model revealed no relation between natural resistance against the bacteria and the activation of macrophages which was evaluated on the basis of releasing capacities of prostaglandin E2 and superoxide anion. The PAM model suggested that TNF-alpha and GM-CSF could activate PAM to restrict the intracellular growth of the bacteria, probably not through the superoxide anion release, but through the myeloperoxidasae-halide system. It was also found that rifamycins in combination with clarithromycin could have a good bactericidal effect in the PAM-model of the infection. Clinical evaluations suggested that defect in local pulmonary defense, such as healed pulmonary tuberculous lesions, pneumoconiosis, and COPD was more important predisposing factor than defect in systemic defense in the development of PMAC. Most patients having PMAC without predisposing factors are elderly women, the reason of which is the most important question to be answered in the future studies.

Animals↗
PubMed2006

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

Editorial↗
PubMed2006

[The Haplotype Map of the human genome: a revolution in the genetics of complex diseases].

More than 99.9 % of the sequence is identical when comparing the DNA from two individuals. The remaining 0.1 % is responsible, along with other factors such as the environment, for the risk level of developing complex diseases (such as asthma, diabetes or cancer) or for the different pharmacological response to drugs. Despite the incredible advances in genomics in the past few years, identifying the variants involved remains difficult because of the prodigious amount of information to process. The recent completion of the Haplotype Map of the human genome has raised great hopes in the field as it is expected to help reduce the complexity of association studies and thus accelerate the discovery of genes associated with complex diseases. This review details the rationale behind the HapMap project, gives a summary of the results and also describes potential applications of the Haplotype Map.

Asthma↗
PubMed2006

[Researches on genetics and genetic epidemiology of common complex diseases: challenge and strategies].

With the rapid development of human genome project, increased genetic and population-based association studies are focused on the identification of the underlying susceptibility genes and contributions from gene-environment interaction to common complex diseases. Whole-genome association study with high-density single nucleotide polymorphisms is one of the most important milestones in that process. However, problems still exist in study design, data processing, and results interpretation. Large-scale cohort study or population-based case-control design with sufficient statistical power, new approaches to assess the gene-gene and gene-environment interactions, as guarantee of the consistency and replicability of these researches are crucial in the exploration of the causes of these common complex diseases.

Genetic Markers↗
PubMed2003

"Are we there yet?": Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits.

Although mathematical relationships can be proven by deductive logic, biological relationships can only be inferred from empirical observations. This is a distinct disadvantage for those of us who strive to identify the genes involved in complex diseases and quantitative traits. If causation cannot be proven, however, what does constitute sufficient evidence for causation? The philosopher Karl Popper said, "Our belief in a hypothesis can have no stronger basis than our repeated unsuccessful critical attempts to refute it." We believe that to establish causation, as scientists, we must make a serious attempt to refute our own hypotheses and to eliminate all known sources of bias before association becomes causation. In addition, we suggest that investigators must provide sufficient data and evidence of their unsuccessful efforts to find any confounding biases. In this editorial, we discuss what "causation" means in the context of complex diseases and quantitative traits, and we suggest guidelines for steps that may be taken to address possible confounders of association before polymorphisms may be called "causative."

Cystic Fibrosis↗
PubMedDate not supplied

Immune deposits and immune complex disease.

Presence in tissues of immune deposits containing antigens, antibodies and complement is the hallmark of immune complex disease. In the Review the present concepts concerning the pathogenesis of inflammatory injury associated with immune deposits resulting from a local deposition of circulating immune complexes or formed 'in situ' are discussed.

Animals↗
PubMed2002

Single nucleotide polymorphism seeking long term association with complex disease.

Successful investigation of common diseases requires advances in our understanding of the organization of the genome. Linkage disequilibrium provides a theoretical basis for performing candidate gene or whole-genome association studies to analyze complex disease. However, to constructively interrogate SNPs for these studies, technologies with sufficient throughput and sensitivity are required. A plethora of suitable and reliable methods have been developed, each of which has its own unique advantage. The characteristics of the most promising genotyping and polymorphism scanning technologies are presented. These technologies are examined both in the context of complex disease investigation and in their capacity to face the unique physical and molecular challenges (allele amplification, loss of heterozygosity and stromal contamination) of solid tumor research.

Biotechnology↗
PubMed2001

Conditional linkage disequilibrium analysis of a complex disease superlocus, IDDM1 in the HLA region, reveals the presence of independent modifying gene effects influencing the type 1 diabetes risk encoded by the major HLA-DQB1, -DRB1 disease loci.

Type 1 diabetes mellitus is a common disease with a complex mode of inheritance. Its aetiology is underpinned by a major locus, insulin-dependent diabetes mellitus 1 (IDDM1) in the human leukocyte antigen (HLA) region of chromosome 6p21, and an unknown number of loci of lesser individual effect. In linkage analyses IDDM1 is a single peak, but it is evident that the linkage is caused by allelic variation of three adjacent genes in a 75 kb region, namely the class II genes, HLA-DRB1, -DQA1 and -DQB1. However, even these three genes may not explain all of the HLA association. We investigated, in the founder population of Sardinia, whether non-DQ/DR polymorphic markers within a 9.452 Mb region encompassing the whole HLA complex further influence the disease risk, after taking into account linkage disequilibrium with the disease loci HLA-DQB1, -DQA1 and -DRB1. We generalized the conditional association test, the haplotype method, to detect marker associations that are independent of the main DR/DQ disease associations. Three regions were identified as risk modifiers. These associations were not only independent of the polymorphic exon 2 sequences of HLA-DQB1, -DQA1 and -DRB1, but also independent of each other. The individual contributions of these risk modifiers were relatively modest but their combined impact was highly significant. Together, alleles of single nucleotide polymorphisms at the DMB and DOB genes, and the microsatellite locus TNFc, identified approximately 40% of Sardinian DR3 haplotypes as non-predisposing. This conditional analysis approach can be applied to any chromosome region involved in the predisposition to complex traits.

Chromosome Mapping↗
PubMed1984

Antibody affinity and acute immune complex disease.

The affinity of anti-BSA antibody was measured daily in rabbits with acute immune complex disease. Affinity values increased with time (r = 0.87: p less than 0.01). Antibody affinity before antigen elimination was 5.3 +/- 0.7 X 10(5)M-1 (Mean +/- SEM, n = 19); affinity after antigen elimination was 9.6 +/- 1.4 X 10(5)M-1 (n = 7). (p less than 0.01: Student's t-test). At the time serum creatinine was elevated antibody affinity was low averaging 7.6 +/- 1.24 X 10(5)M-1 (n = 9). These findings support the hypothesis that complexes of low affinity antibody and antigen may participate in acute immune complex injury.

Animals↗
PubMed1994

Role of serological tests in the diagnosis of immune complex disease in infection of ventriculoatrial shunts for hydrocephalus.

Seven cases of ventriculoatrial shunt infection with immune complex disease are reported in order to demonstrate the usefulness of measurement of levels of specific antibody to Staphylococcus epidermidis in diagnosis. Blood and cerebrospinal fluid cultures gave misleading results, and there was initial doubt about the diagnosis in all seven cases. All showed grossly elevated titres of antibody to Staphylococcus epidermidis, with raised serum C-reactive protein levels and depressed complement levels. Measurement of antibody to Staphylococcus epidermidis enables the diagnosis of chronic ventriculoatrial shunt infection to be made rapidly and reliably.

Adolescent↗
PubMed1998

Mycobacterium tuberculosis infection and disease are not associated with protection against subsequent disseminated M. avium complex disease.

OBJECTIVE: To determine the relationship between Mycobacterium tuberculosis infection and disease and subsequent disseminated M. avium complex (MAC) disease in HIV-infected persons. DESIGN: A prospective observational cohort study. SETTING: The AIDS Linked to the Intravenous Experience (ALIVE) cohort of injecting drug users and the Johns Hopkins Hospital Adult HIV Clinic (JHHAHC). PARTICIPANTS: HIV-infected persons aged > 18 years with CD4 lymphocytes < 100 x 10(6)/l were followed between July 1989 and 31 October 1996. There were 182 persons in the ALIVE cohort and 1129 persons in JHHAHC who met these criteria. MAIN OUTCOME MEASURE: The relative risk of disseminated MAC was determined according to a history of prior opportunistic infection, MAC prophylaxis, antiretroviral therapy, M. tuberculosis infection or disease, race, sex, and injecting drug use. RESULTS: Amongst the 30 patients with active tuberculosis, eight developed disseminated MAC, compared with 208 cases of disseminated MAC amongst 1148 patients without prior M. tuberculosis infection or disease [relative risk (RR), 1.5; 95% confidence interval (CI), 0.8-2.7; P=0.2]. Amongst the 10 patients with extrapulmonary tuberculosis, five developed disseminated MAC (RR, 2.8; 95% CI, 1.5-5.2; P=0.02). Injecting drug use was associated with a decreased risk of disseminated MAC (RR, 0.7; 95% CI, 0.6-0.9; P=0.007). In a logistic regression analysis, disseminated MAC was significantly associated with extrapulmonary tuberculosis and other opportunistic disease, whereas antibiotic prophylaxis and injecting drug use were protective. CONCLUSIONS: A history of M. tuberculosis infection or disease was not associated with protection against subsequent disseminated MAC disease in HIV-infected persons. However, persons with extrapulmonary tuberculosis were at increased risk for disseminated MAC, particularly at low CD4 cell levels.

AIDS-Related Opportunistic Infections↗
PubMed1987

The effect of rheumatoid factor on the clearance of endogenous immune complexes formed in low-affinity mice during the induction of immune complex disease.

Intravenous injection of rheumatoid factor (RF) had a marked effect on the clearance kinetics of immune complexes (IC) formed in vivo during induction of chronic immune complex disease in low-affinity mice. RF resulted in a significant increase in IC level and clearance time in 64% of mice with circulating IC after antigen injection, suggesting that RF may alter the handling of potentially pathogenic IC which localize in the renal capillaries causing glomerulonephritis.

Animals↗
PubMed1977

Immune complex disease of the skin.

The physician can now recognize clinically and histopathologically the cutaneous manifestations of immune complex disease. The usual clinical environment in which this type of reaction occurs has been very specifically delineated. Studies of immunoglobulins, complement components, and B cells in the blood may confirm the nature of the reaction. Special studies of cryoproteins of C1q precipitin or radioimmunoassay procedures may demonstrate directly the complexes in the blood. Biopsy of skin for immunofluorescence is confirmative of the skin disease and the presence of immune complexes. Biopsy of normal skin may be prognostic and indicate severity of the disease. Lesions may be induced by epinephrine, trauma, and controlled imflammation for clinical and pathologic study and confirmation of diagnosis. Treatment of the disease with corticosteroids, sulfapyridine, nicotinic acid, and antimalarial drugs may be useful. Clofazimine is an intriguing experimental drug. Plasmaphoresis has worked well with some patients.

Antigen-Antibody Complex↗
PubMed1979

Immune complex disease associated with Peroben intake.

The clinical history and biological investigations of a patient presenting an immune complex disease induced by Peroben are reported. Biological signs were those of a drug-induced lupus syndrome. A provocation test allowed disclosure of its pathomechanism, since during Peroben intake a high C1q binding activity occurred and later regressed, while deposits of IgM and C3 were evidenced in the vessel walls. Complete or partial thrombosis succeeded accompanying a leukocytoclastic vasculitis.

Adult↗
PubMed2005

Sibship T2 association tests of complex diseases for tightly linked markers.

For population case-control association studies, the false-positive rates can be high due to inappropriate controls, which can occur if there is population admixture or stratification. Moreover, it is not always clear how to choose appropriate controls. Alternatively, the parents or normal sibs can be used as controls of affected sibs. For late-onset complex diseases, parental data are not usually available. One way to study late-onset disorders is to perform sib-pair or sibship analyses. This paper proposes sibship-based Hotelling's T2 test statistics for high-resolution linkage disequilibrium mapping of complex diseases. For a sample of sibships, suppose that each sibship consists of at least one affected sib and at least one normal sib. Assume that genotype data of multiple tightly linked markers/haplotypes are available for each individual in the sample. Paired Hotelling's T2 test statistics are proposed for high-resolution association studies using normal sibs as controls for affected sibs, based on two coding methods: 'haplotype/allele coding' and 'genotype coding'. The paired Hotelling's T2 tests take into account not only the correlation among the markers, but also take the correlation within each sib-pair. The validity of the proposed method is justified by rigorous mathematical and statistical proofs under the large sample theory. The non-centrality parameter approximations of the test statistics are calculated for power and sample size calculations. By carrying out power and simulation studies, it was found that the non-centrality parameter approximations of the test statistics were accurate. By power and type I error analysis, the test statistics based on the 'haplotype/allele coding' method were found to be advantageous in comparison to the test statistics based on the 'genotype coding' method. The test statistics based on multiple markers can have higher power than those based on a single marker. The test statistics can be applied not only for bi-allelic markers, but also for multi-allelic markers. In addition, the test statistics can be applied to analyse the genetic data of multiple markers which contain double heterozygotes--that is, unknown linkage phase data. An SAS macro, Hotel_sibs.sas, is written to implement the method for data analysis.

Diabetes Mellitus↗
PubMed2004

Nonreplication in genetic studies of complex diseases--lessons learned from studies of osteoporosis and tentative remedies.

Inconsistent results have accumulated in genetic studies of complex diseases/traits over the past decade. Using osteoporosis as an example, we address major potential factors for the nonreplication results and propose some potential remedies. Over the past decade, numerous linkage and association studies have been performed to search for genes predisposing to complex human diseases. However, relatively little success has been achieved, and inconsistent results have accumulated. We argue that those nonreplication results are not unexpected, given the complicated nature of complex diseases and a number of confounding factors. In this article, based on our experience in genetic studies of osteoporosis, we discuss major potential factors for the inconsistent results and propose some potential remedies. We believe that one of the main reasons for this lack of reproducibility is overinterpretation of nominally significant results from studies with insufficient statistical power. We indicate that the power of a study is not only influenced by the sample size, but also by genetic heterogeneity, the extent and degree of linkage disequilibrium (LD) between the markers tested and the causal variants, and the allele frequency differences between them. We also discuss the effects of other confounding factors, including population stratification, phenotype difference, genotype and phenotype quality control, multiple testing, and genuine biological differences. In addition, we note that with low statistical power, even a "replicated" finding is still likely to be a false positive. We believe that with rigorous control of study design and interpretation of different outcomes, inconsistency will be largely reduced, and the chances of successfully revealing genetic components of complex diseases will be greatly improved.

Animals↗
PubMed2001

Finding genes influencing susceptibility to complex diseases in the post-genome era.

During the last decade, hundreds of genes that harbor mutations causing simple Mendelian disorders have been identified using a combination of linkage analysis and positional cloning techniques. Traditional approaches to gene mapping have been largely unsuccessful in mapping genes influencing so-called 'complex' genetic diseases, however, because of low power and other factors. Complex genetic diseases do not display simple Mendelian patterns of inheritance, although genes do have an influence and close relatives of probands consequently have an increased risk. These disorders are thought to be due to the combined effects of variation at multiple interacting genes and the environment. Complex diseases have a significant impact on human health because of their high population incidence (unlike simple Mendelian disorders, which tend to be rare). New techniques are being developed aimed specifically at mapping genes conferring susceptibility to complex diseases. A project aimed at mapping genes influencing susceptibility to a complex disease may be undertaken in several stages: establishing a genetic basis for the disease in one or more populations; measuring the distribution of gene effects; studying statistical power using models; carrying out marker-based mapping studies using linkage or association. Quantitative genetic models can be used to estimate the heritability of a complex (polygenic) disease, as well as to predict the distribution of gene effects and to test whether one or more quantitative trait loci (QTLs) exist. Such models can be used to predict the power of different mapping approaches, but are often unrealistic and therefore provide only approximate predictions. Linkage analyses, association studies and family-based association tests are all hindered by low power and other specific problems. Association studies tend to be more powerful but can generate spurious associations due to population admixture. Alternative strategies for association mapping include the use of recent founder populations or unique isolated populations that are genetically homogeneous, and the use of unlinked markers (so-called genomic controls) to assign different regions of the genome of an admixed individual to particular source populations. Linkage disequilibrium observed in a sample of unrelated affected and normal individuals can also be used to fine-map a disease susceptibility locus in a candidate region. New Bayesian strategies make use of an annotated human genome sequence to further refine the position of a candidate disease susceptibility locus.

Genetic Diseases, Inborn↗